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The US Environmental Protection Agency (US EPA) initiated planning in 2007 and conducted field work in 2011 for the first National Wetland Condition Assessment (NWCA) as part of the National Aquatic Resource Surveys (NARS). It complements the US Fish and Wildlife Service (USFWS) National Wetland Status and Trends (S&T) program that estimates wetland acres nationally. The NWCA used a stratified, unequal probability survey design based on wetland information from S&T plots to select 900 sites for the conterminous 48 states. Based on site evaluation information, the NWCA estimates that there are 94.9 (± 6.20) million acres of wetlands in the NWCA target wetland population (reported in acres to be consistent with S&T). Not all of the estimated target population acres could be sampled due to accessibility and field issues. Based on the sites that could be sampled, the sampled population for the NWCA is estimated to be 62.2 (± 5.28) million acres of wetland area. Landowner denial for access was the main reason (24.7% ± 3.5%) for the sampled population being smaller than the target population, and physical inaccessibility was the second reason (6.8% ± 2.1%). The NWCA 2011 survey design was successful in enabling a national survey for wetland condition to be conducted and coordinated with the USFWS S&T survey of wetland extent. The NWCA 2016 survey design has been modified to address sample frame issues resulting from the difference in S&T focusing only on national estimates and NWCA focusing on national and regional estimates.

Passive acoustic surveys provide a convenient and cost-effective way to monitor animal populations, and methods for conducting and analysing such surveys are undergoing rapid development. However, no standard metric exists to evaluate the proposed changes. Furthermore, the metrics that are commonly used are specific to a single stage of the survey workflow, and may not reflect the overall effects of a design choice. Here, we attempt to define the effectiveness of acoustic surveys conducted in two common frameworks of population inference—occupancy modelling and spatially explicit capture-recapture (SCR). Specifically, we investigate precision as a possible metric of survey performance, but we observe that it does not lead to generally optimal designs in occupancy modelling. In contrast, the precision of the SCR density estimate can be optimised with fewer experiment-specific parameters. We illustrate these issues using simulations. We further demonstrate how SCR precision can be used to evaluate design choices on a field survey of little spotted kiwi (Apteryx owenii). We compare call recognition by software and human experts. The resulting tradeoff between missed calls and faster data throughput was accurately captured with the proposed metric, while common metrics failed to identify optimal improvements and could be inflated by deleting data. Due to the flexibility of SCR framework, the approach presented here can be applied to a wide range of different survey designs. As the precision is directly related to the power of subsequent inference, this metric evaluates design choices at the application level and captures tradeoffs that are missed by stage-specific metrics, enabling reliable comparison of survey methods.

Surveys for long-term monitoring programs managing natural resources often incorporate sampling design complexity. However, design weights are often ignored in trend models of data from complex sampling designs. Generalized random tessellation stratified samples of a simulated population of lakes are selected with various levels of survey design complexity, and three trend approaches are compared. We compare an unweighted trend model, linear regression models of the trend in design-based estimates of annual status, and a probability-weighted iterative generalized least squares (PWIGLS) approach with a linearization variance. The bias and confidence interval coverage of the trend estimate and the size and power of the trend test are used to evaluate weighted and unweighted approaches. We find that the unweighted approach often outperforms the other trend approaches by providing high power for trend detection and nominal confidence interval coverage of the true trend regression parameter. We also find that variance composition and revisit design structure affect the performance of the PWIGLS estimator. When a subpopulation exhibiting an extreme trend is sampled disproportionately to its occurrence in the population, the unweighted approach may produce biased estimates of trend with poor confidence interval coverage. We recommend considering variance composition and potential subpopulation trends when selecting sampling designs and trend analysis approaches.

Non-response is a common source of error in many surveys. Because surveys often are costly instruments, quality-cost trade-offs play a continuing role in the design and analysis of surveys. The advances of telephone, computers, and Internet all had and still have considerable impact on the design of surveys. Recently, a strong focus on methods for survey data collection monitoring and tailoring has emerged as a new paradigm to efficiently reduce non-response error. Paradata and adaptive survey designs are key words in these new developments. Prerequisites to evaluating, comparing, monitoring, and improving quality of survey response are a conceptual framework for representative survey response, indicators to measure deviations thereof, and indicators to identify subpopulations that need increased effort. In this paper, we present an overview of representativeness indicators or R-indicators that are fit for these purposes. We give several examples and provide guidelines for their use in practice. La non-réponse est une source d'erreur importante dans de nombreuses enquêtes. Étant donné que les enquêtes sont souvent des opérations coûteuses, le compromis entre qualité et coût est omniprésent dans leur conception aussi bien que dans leur analyse. Les progrès du téléphone, des ordinateurs et d'internet tous ont eu, et ont encore, un impact considérable sur la conception des enquêtes. Récemment, l'accent a été mis sur les méthodes de collecte de données d'enquêtes de surveillance et l'adaptation est apparue comme un nouveau paradigme réduisant de façon efficace les erreurs liées à la non-réponse. «Paradonnées» (paradata) et plans de sondage adaptatifs sont les mots-clés de ces nouveaux développements. Les conditions préalables à l'évaluation, à la comparaison, à la surveillance et à l'amélioration de la qualité de la réponse du sondage sont un cadre conceptuel pour l'étude de la représentativité des résultats d'enquêtes et de leurs mesures de déviation, ainsi que pour l'identification des sous-populations requérant un effort accru. Dans cet article, nous présentons un aperçu des indicateurs de représentativité ou R-indicateurs qui sont propres à ces fins. Nous donnons plusieurs exemples, et des lignes directrices pour leur mise en pratique.

The Likert-type scale is a widely used psychometric instrument for measuring attitudes, opinions, or perceptions in research contexts. It presents respondents with a series of statements accompanied by symmetrical response options, typically structured on a five-point scale ranging from “Strongly Disagree” to “Strongly Agree”. Each point on the scale represents a gradation of agreement or sentiment, allowing researchers to transform subjective responses into quantifiable data for statistical analysis and interpretation.

Collecting, Managing, and Assessing Data Using Sample Surveys provides a thorough, step-by-step guide to the design and implementation of surveys. Beginning with a primer on basic statistics, the first half of the book takes readers on a comprehensive tour through the basics of survey design. Topics covered include the ethics of surveys, the design of survey procedures, the design of the survey instrument, how to write questions and how to draw representative samples. Having shown readers how to design surveys, the second half of the book discusses a number of issues surrounding their implementation, including repetitive surveys, the economics of surveys, web-based surveys, coding and data entry, data expansion and weighting, the issue of non-response, and the documenting and archiving of survey data. The book is an excellent introduction to the use of surveys for graduate students as well as a useful reference work for scholars and professionals.

Conjoint analysis is a common tool for studying political preferences. The method disentangles patterns in respondents’ favorability toward complex, multidimensional objects, such as candidates or policies. Most conjoints rely upon a fully randomized design to generate average marginal component effects (AMCEs). They measure the degree to which a given value of a conjoint profile feature increases, or decreases, respondents’ support for the overall profile relative to a baseline, averaging across all respondents and other features. While the AMCE has a clear causal interpretation (about the effect of features), most published conjoint analyses also use AMCEs to describe levels of favorability. This often means comparing AMCEs among respondent subgroups. We show that using conditional AMCEs to describe the degree of subgroup agreement can be misleading as regression interactions are sensitive to the reference category used in the analysis. This leads to inferences about subgroup differences in preferences that have arbitrary sign, size, and significance. We demonstrate the problem using examples drawn from published articles and provide suggestions for improved reporting and interpretation using marginal means and an omnibus F-test. Given the accelerating use of these designs in political science, we offer advice for best practice in analysis and presentation of results.

Every three years, researchers with interest and expertise in transport survey methods meet to improve and influence the conduct of surveys that support transportation planning, policy making, modelling, and monitoring related issues for urban, regional, intercity, and international person, vehicle, and commodity movements. This book compiles the critical thinking on priority topics in contemporary transport policy and planning contexts. The contributed papers cover two key themes related to types of decision-making of importance to the development of data collection on both passenger travel and freight movements: the first theme, Selecting the Right Survey Method, acknowledges the fact that transport survey methods are evolving to meet both changing uses of transport survey data and the challenges of conducting surveys within contemporary society. The second theme, Supporting Transport Planning and Policy, recognizes that the demands on transportation data programs to support decision-making for transport planning and policy making clearly have evolved.The chapters have been selected with particular emphasis on the challenges of the near and medium term future to the design of transport surveys. Rapidly evolving problems and policy contexts are compelling transport researchers to advance the state-of-the-art of methods, tools, strategies and protocols, while assuring the stability and coherence of the very data from which trends can be tracked and understood and on which important decisions can be made.

Purpose: The transgender community is a diverse group that requires unique consideration in the healthcare setting. However, several studies have suggested that their needs are not currently being met by our medical system. Although the reason for this discrepancy is likely multifactorial, inadequate training of healthcare professionals to manage this population has been cited as a contributing factor. Methods: To evaluate the role that Canadian medical schools play in addressing these proposed deficits, program administrators were invited to provide curricular information detailing their delivery of transgender health, and medical students were surveyed to assess the impact of current curricula on their knowledge, attitudes, and experiences with regard to transgender health. Results: Six of fourteen schools provided curricular information about their instruction in transgender health and wide variation was found; 255/1152 University of British Columbia (UBC) students and 155/2358 students from eight other Canadian medical schools responded to the survey. Greater than 95% of responders agreed that transgender issues are important and should be addressed by physicians. However, fewer than 10% of students felt that they were sufficiently knowledgeable to do so. At UBC, there was no significant improvement in the self-reported knowledge levels after receiving the transgender-related curricula, and only 24% of students felt the topic was proficiently taught. Conclusion: This study showed that the majority of students who responded do not feel comfortable addressing the needs of transgender individuals in a healthcare setting and suggests that a reevaluation of related curricula may be warranted.

Establishing contact is an important part of the response process and effective interviewer calling behaviours are critical in achieving contact and subsequent co-operation.The paper investigates best times of contact for different types of households and the influence of the interviewer on establishing contact. Recent developments in the survey data collection process have led to the collection of so-called field process data or paradata, which greatly extend the basic information on interviewer calls. The paper develops a multilevel discrete time event history model based on interviewer call record data to predict the likelihood of contact at each call. The results have implications for survey practice and inform the design of effective interviewer calling times, including responsive survey designs.